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A Consideration of Biomarkers to be Used for Evaluation of Inflammation in Human Nutritional Studies


British Journal of Nutrition. 2013;109(Suppl 1):S1-S34

To monitor inflammation in a meaningful way, the markers used must be valid: they must reflect the inflammatory process under study and they must be predictive of future health status. The overall aim of this article is to attempt to identify robust and predictive markers, or patterns or clusters of markers, which can be used to assess inflammation in human nutrition studies in the general population. Inflammation is a normal process and there are a number of cells and mediators involved. These include several blood cell types and numerous peptides, and proteins and lipid mediators that circulate in the bloodstream. These markers are involved in, or are produced as a result of, the inflammatory process irrespective of its trigger and its location. They are common to all inflammatory diseases, to acute and chronic inflammatory responses, and to both high-grade and low-grade inflammation. Currently, there is no consensus as to which markers of inflammation best represent low-grade inflammation or differentiate between acute and chronic inflammation or between the initiation, propagation and resolution phases of inflammatory responses. There are a number of modifying factors that affect the concentration of an inflammatory marker at a given time, including age, diet, body fatness, physical (in)activity, sex, smoking, genetics and microbiota composition. Measuring the concentration of inflammatory markers in the bloodstream under basal conditions is probably less informative as data related to the concentration change in response to a challenge. A number of inflammatory challenges reflecting metabolic stress, infection, and tissue damage have been described. However, many of these challenges are poorly standardised. Patterns and clusters may be important as robust biomarkers of inflammation. Therefore, it is likely that a combination of multiple inflammatory markers and integrated readouts based upon kinetic analysis following defined challenges will be the most informative biomarker of inflammation.

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